Blockchain Integration in UAV Networks: Performance Metrics and Analysis.

Autor: Hossain MI; School of Systems & Computing, University of New South Wales, Canberra, ACT 2600, Australia., Tahtali M; School of Engineering & Technology, University of New South Wales, Canberra, ACT 2600, Australia., Turhan U; School of Science, University of New South Wales, Canberra, ACT 2600, Australia., Biswas K; Peter Faber Business School, Australian Catholic University, Brisbane, QLD 4014, Australia.; Department of Computer Science and Engineering, Daffodil International University, Dhaka 1216, Bangladesh.

Publikováno v: Sensors (Basel, Switzerland) [Sensors (Basel)] 2024 Dec 06; Vol. 24 (23). Date of Electronic Publication: 2024 Dec 06.

Sparse Bayesian Learning for EEG Source Localization

Autor: Saha, Sajib, de Hoog, Frank, Nesterets, Ya. I., Rana, Rajib, Tahtali, M., Gureyev, T. E.

Purpose: Localizing the sources of electrical activity from electroencephalographic (EEG) data has gained considerable attention over the last few years. In this paper, we propose an innovative source localization method for EEG, based on Sparse Baye

Externí odkaz: http://arxiv.org/abs/1501.04621

EEG source localization using a sparsity prior based on Brodmann areas

Autor: Saha, S., Nesterets, Ya. I., Rana, Rajib, Tahtali, M., de Hoog, Frank, Gureyev, T. E.

Localizing the sources of electrical activity in the brain from Electroencephalographic (EEG) data is an important tool for non-invasive study of brain dynamics. Generally, the source localization process involves a high-dimensional inverse problem t

Externí odkaz: http://arxiv.org/abs/1406.2434

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